Bridging to a hybrid cloud data services architecture

• Provides a tiered data environment that bridges two or more public and/or private clouds

• May bridge two or more of distinct cloud data services technologies, including but not limited to Spark, Hadoop, data warehouses, graph databases, NoSQL databases, multi-workload SQL databases , open-source databases, data refineries, and predictive analytics

What is a hybrid cloud data services architecture?

Benefits of bridging to a hybrid cloud data services architecture

• Enables mix-and-match deployment of complementary data technologies in a unified, managed cloud architecture

• Provides flexibility for each data technology to be fit to the functional and deployment role for which it’s best suited

• Supports end-to-end scaling and performance optimization as each node, cluster, and other component can be independently optimized and grow to suit its own workloads.

• Allows data to be persisted in diverse physical and logical formats across a virtualized cloud of interconnected memory and disk that can be elastically scaled

Chief applications of hybrid cloud data services

Logical data warehouse

Multi-tier hybrid architecture supporting data acquisition, refinement, governance, analysis, and delivery of business intelligence; usually focused on structured data

Data lake

Multi-tier hybrid architecture supporting data acquisition, preparation, statistical modeling and interactive exploration by data scientists; usually focused on multistructured data

Operational data hub

Multi-tier hybrid architecture supporting transactional data applications, indexing, query and management

How do you bridge to a logical data warehouse in the cloud?

• Rapidly deploy large- scale managed cloud data warehouses, with flexible options for both volume and processing speed

• Implement unified architecture that enables hybrid data processing between on-premises and cloud

• Integrate with cloud and on-premises data services to create a seamless data management platform

• Blend data from multiple sources, combining them into a unified view of the business

• Ensure data quality via simple data preparation and movement cloud services

• Translate JSON documents into a schema (or set of tables) the LDW understands for reporting and analytics on NoSQL data

• Combine columnar technology with in-database analytics

Sign up for dashDBwith DataWorksFree 3-month trialhttp://ibm.co/ibm-dashdb-trial

• Fully managed dedicated-instance LDW service (IBM dashDB Enterprise 64.1)

• Data integration, refinery and workflow service (IBM DataWorks Personal Edition, DataWorks Forge)

• IBM SaaS Startup Advisory – 20 hours of free services

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How do you bridge to a data lake in the cloud?

• Work with NoSQL Data and extend insights with more advanced analytics

• Implement high-performance, high-availability NoSQL cloud database

• Use fully-managed and secured Spark environment accessible on-demand or via reserved enterprise instances

• Develop in Spark Notebooks for advanced analytics on NoSQL/JSON data

• Implement built-in Spark-NoSQL/JSON connectors

• Utilize in-memory architecture for fast operations

• Perform interactive and micro-batch streaming analytics

• Transform and filter data before write it back into various data sources

• Load and analyze business data in memory

Sign up for ApacheSpark and CloudantFree 3-month trialhttp://ibm.co/ibm-spark-trial http://ibm.co/ibm-cloudant-trial

• Fully managed dedicated-instance data lake service IBM Analytics for Apache Spark Reserved Enterprise with IBM Cloudant Dedicated SMB

• IBM SaaS Startup Advisory – 20 hours of free services

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• Deploy operational database in the cloud to complement on-premises databases

• Maintain full administrative and operational control over the hosted cloud database

• Allow cloud provider to install database hardware and software, apply OS patches, updates hardware, provision within cloud data centers, scale without the concerns of managing physical infrastructure

• Enable technical and nontechnical users to extract value from data quickly and easily

• Create and control workflow activities from an application

• Integrate with cloud and on-premises data services to create a seamless data management platform

• Blend data from multiple sources, combining them into a unified view of the business

• Ensure data quality via simple data preparation and movement cloud services

How do you bridge to anoperational data hub in the cloud?

Sign up for DB2 onCloud with DataWorksFree 3-month trialhttp://ibm.co/ibm-db2-trial http://ibm.co/ibm-dataworks-trial

• Fully managed dedicated-instance Operational Data Hub service (IBM DB2 Standard on Cloud Small, DB2 Workgroup Server Edition License bundled with Native Encryption)

• Data integration, refinery and workflow service (IBM DataWorks Personal Edition)

• IBM SaaS Startup Advisory – 20 hours of free services #DB2free

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